Large language models (LLMs) are a special class of pretrained language models (PLMs)
obtained by scaling model size, pretraining corpus and computation. LLMs, because of their …

The advent of large language models marks a revolutionary breakthrough in artificial
intelligence. With the unprecedented scale of training and model parameters, the capability …

There is an increasing interest in developing artificial intelligence (AI) systems to process
and interpret electronic health records (EHRs). Natural language processing (NLP) powered …

This paper presents an exhaustive quantitative and qualitative evaluation of Large
Language Models (LLMs) for Knowledge Graph (KG) construction and reasoning. We …

Relation extraction (RE) involves identifying the relations between entities from underlying
content. RE serves as the foundation for many natural language processing (NLP) and …

Recent years have seen a paradigm shift in NLP towards using pretrained language models
({PLM}) for a wide range of tasks. However, there are many difficult design decisions to …

There is an increasing interest in developing artificial intelligence (AI) systems to process
and interpret electronic health records (EHRs). Natural language processing (NLP) powered …

Identification of named entities from legal texts is an essential building block for developing
other legal Artificial Intelligence applications. Named Entities in legal texts are slightly …

We present KPI-BERT, a system which employs novel methods of named entity recognition
(NER) and relation extraction (RE) to extract and link key performance indicators (KPIs), eg" …

Cross-lingual named entity recognition (CrossNER) faces challenges stemming from
uneven performance due to the scarcity of multilingual corpora, especially for non-English …